A 40-Year Cohort Study of Evolving Hypothalamic Dysfunction in Infants and Young Children (<3 years) with Optic Pathway Gliomas

Despite high survival, paediatric optic pathway hypothalamic gliomas are associated with significant morbidity and late mortality. Those youngest at presentation have the worst outcomes. We aimed to assess presenting disease, tumour location, and treatment factors implicated in the evolution of neuroendocrine, metabolic, and neurobehavioural morbidity in 90 infants/children diagnosed before their third birthday and followed-up for 9.5 years (range 0.5–25.0). A total of 52 (57.8%) patients experienced endo-metabolic dysfunction (EMD), the large majority (46) of whom had hypothalamic involvement (H+) and lower endocrine event-free survival (EEFS) rates. EMD was greatly increased by a diencephalic syndrome presentation (85.2% vs. 46%, p = 0.001)), H+ (OR 6.1 95% CI 1.7–21.7, p 0.005), radiotherapy (OR 16.2, 95% CI 1.7–158.6, p = 0.017) and surgery (OR 4.8 95% CI 1.3–17.2, p = 0.015), all associated with anterior pituitary disorders. Obesity occurred in 25% of cases and was clustered with the endocrinopathies. Neurobehavioural deficits occurred in over half (52) of the cohort and were associated with H+ (OR 2.5 95% C.I. 1.1–5.9, p = 0.043) and radiotherapy (OR 23.1 C.I. 2.9–182, p = 0.003). Very young children with OPHG carry a high risk of endo-metabolic and neurobehavioural comorbidities which deserve better understanding and timely/parallel support from diagnosis to improve outcomes. These evolve in complex, hierarchical patterns over time whose aetiology appears predominantly determined by injury from the hypothalamic tumour location alongside adjuvant treatment strategies

On the use of symmetry in configurational analysis for the simulation of disordered solids

The starting point for a quantum mechanical investigation of disordered systems usually implies calculations on a limited subset of configurations, generated by defining either the composition of interest or a set of compositions ranging from one end member to another, within an appropriate supercell of the primitive cell of the pure compound. The way in which symmetry can be used in the identification of symmetry independent configurations (SICs) is discussed here. First, Pólya's enumeration theory is adopted to determine the number of SICs, in the case of both varying and fixed composition, for colors numbering two or higher. Then, De Bruijn's generalization is presented, which allows analysis of the case where the colors are symmetry related, e.g. spin up and down in magnetic systems. In spite of their efficiency in counting SICs, neither Pólya's nor De Bruijn's theory helps in solving the difficult problem of identifying the complete list of SICs. Representative SICs are obtained by adopting an orderly generation approach, based on lexicographic ordering, which offers the advantage of avoiding the (computationally expensive) analysis and storage of all the possible configurations. When the number of colors increases, this strategy can be combined with the surjective resolution principle, which permits the efficient generation of SICs of a problem in |R| colors starting from the ones obtained for the (|R| − 1)-colors case. The whole scheme is documented by means of three examples: the abstract case of a square with C4v symmetry and the real cases of the garnet and olivine mineral families

Symmetry and random sampling of symmetry independent configurations for the simulation of disordered solids

A symmetry-adapted algorithm producing uniformly at random the set of symmetry independent configurations (SICs) in disordered crystalline systems or solid solutions is presented here. Starting from Pólya's formula, the role of the conjugacy classes of the symmetry group in uniform random sampling is shown. SICs can be obtained for all the possible compositions or for a chosen one, and symmetry constraints can be applied. The approach yields the multiplicity of the SICs and allows us to operate configurational statistics in the reduced space of the SICs. The present low-memory demanding implementation is briefly sketched. The probability of finding a given SIC or a subset of SICs is discussed as a function of the number of draws and their precise estimate is given. The method is illustrated by application to a binary series of carbonates and to the binary spinel solid solution Mg(Al,Fe)2O4

B-type natriuretic peptide-induced delayed modulation of TRPV1 and P2X3 receptors of mouse trigeminal sensory neurons

Important pain transducers of noxious stimuli are small- and medium-diameter sensory neurons that express transient receptor vanilloid-1 (TRPV1) channels and/or adenosine triphosphate (ATP)-gated P2X3 receptors whose activity is upregulated by endogenous neuropeptides in acute and chronic pain models. Little is known about the role of endogenous modulators in restraining the expression and function of TRPV1 and P2X3 receptors. In dorsal root ganglia, evidence supports the involvement of the natriuretic peptide system in the modulation of nociceptive transmission especially via the B-type natriuretic peptide (BNP) that activates the natriuretic peptide receptor-A (NPR-A) to downregulate sensory neuron excitability. Since the role of BNP in trigeminal ganglia (TG) is unclear, we investigated the expression of BNP in mouse TG in situ or in primary cultures and its effect on P2X3 and TRPV1 receptors of patch-clamped cultured neurons. Against scant expression of BNP, almost all neurons expressed NPRA at membrane level. While BNP rapidly increased cGMP production and Akt kinase phosphorylation, there was no early change in passive neuronal properties or responses to capsaicin, \u3b1,\u3b2-meATP or GABA. Nonetheless, 24 h application of BNP depressed TRPV1 mediated currents (an effect blocked by the NPR-A antagonist anantin) without changing responses to \u3b1,\u3b2-meATP or GABA. Anantin alone decreased basal cGMP production and enhanced control \u3b1,\u3b2-meATP-evoked responses, implying constitutive regulation of P2X3 receptors by ambient BNP. These data suggest a slow modulatory action by BNP on TRPV1 and P2X3 receptors outlining the role of this peptide as a negative regulator of trigeminal sensory neuron excitability to nociceptive stimuli. \ua9 2013 Vilotti et al

Interpretable surface-based detection of focal cortical dysplasias:a Multi-centre Epilepsy Lesion Detection study

One outstanding challenge for machine learning in diagnostic biomedical imaging is algorithm interpretability. A key application is the identification of subtle epileptogenic focal cortical dysplasias (FCDs) from structural MRI. FCDs are difficult to visualize on structural MRI but are often amenable to surgical resection. We aimed to develop an open-source, interpretable, surface-based machine-learning algorithm to automatically identify FCDs on heterogeneous structural MRI data from epilepsy surgery centres worldwide. The Multi-centre Epilepsy Lesion Detection (MELD) Project collated and harmonized a retrospective MRI cohort of 1015 participants, 618 patients with focal FCD-related epilepsy and 397 controls, from 22 epilepsy centres worldwide. We created a neural network for FCD detection based on 33 surface-based features. The network was trained and cross-validated on 50% of the total cohort and tested on the remaining 50% as well as on 2 independent test sites. Multidimensional feature analysis and integrated gradient saliencies were used to interrogate network performance. Our pipeline outputs individual patient reports, which identify the location of predicted lesions, alongside their imaging features and relative saliency to the classifier. On a restricted 'gold-standard' subcohort of seizure-free patients with FCD type IIB who had T1 and fluid-attenuated inversion recovery MRI data, the MELD FCD surface-based algorithm had a sensitivity of 85%. Across the entire withheld test cohort the sensitivity was 59% and specificity was 54%. After including a border zone around lesions, to account for uncertainty around the borders of manually delineated lesion masks, the sensitivity was 67%. This multicentre, multinational study with open access protocols and code has developed a robust and interpretable machine-learning algorithm for automated detection of focal cortical dysplasias, giving physicians greater confidence in the identification of subtle MRI lesions in individuals with epilepsy

Pseudouridylation defect due to DKC1 and NOP10 mutations causes nephrotic syndrome with cataracts, hearing impairment, and enterocolitis

Research UK Innovation and Project; Cancer Research U

High-sensitivity monitoring of VOCs in air via FTIR spectroscopy using a multipass gas cell setup

The exposure to volatile organic compounds (VOCs) constitutes a serious environmental health concern. Currently, different typologies of sensors are able to track the VOCs presence in workplaces, but they are limited in terms of chemical selectivity and sensitivity. Here, we apply Infrared (IR) spectroscopy combined to a multipass cell in order to extend the sensitivity of this technique down to the part per million (ppm) level. We calibrate the system for four compounds of interest and finally test the recognition performances on mixture of VOCs